Nobody Wants ML, AI, and Analytics.
Customers and users want a UX that provides indispensable decision support, useful insights, and actionable intelligence—their way.
Before business value can emerge from your data product, there must be adoption, trust, usabilty and utility.
This is the domain of human-centered design.
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Recent Articles by Brian
How to get 1 x 1 research access to users of enterprise data products—when your own company is in the way
Are you a leader in charge of creating innovative ML and analytics solutions within a very large enterprise organization? Getting the “makers” of the solutions talking to real end-users can be extremely difficult. Here’s how to navigate the gatekeepers and bureaucracy so that the data products you spend so much time and money building actually are useful, usable, and valuable.
AI / Product Management / UX Design Predictions for 2021
I’m not putting out a long list of 2021 predictions, but I have a couple that I will mention to you that are on my radar. First, AI/Data Product Management Seems to be Picking Up There seem to be more jobs appearing … Read more
Does an analytical mind block your innovation and creativity?
Data science, analytics, and engineering are in-demand skills, however, when building customer-facing applications and data-driven products, organizations rely on innovation to unlock the power of this data. How can analytical minds practice creativity that leads to innovative solutions?
What’s Wrong with Spotify’s Analytics Emails (a Design/UI/UX Audit)
Today, I’m sharing my impressions of one of Spotify’s analytics touchpoints—a monthly email I receive with a boatload of design choices I mostly hope you will not copy, especially if you’re working in an enterprise capacity. Most of you by now probably know … Read more
Re: Your “Home Depot” Approach to AI/ML
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Better data visualization won’t convince me when to play ⚽️ again
Presenting data and evidence isn’t the same thing as providing indispensable decision support, especially when your insights are experienced in a software application with no Powerpoint deck, narrator, or intimate storytelling.
Designing for AI (UX, UI)
This is an ongoing list of links to articles, slide decks, toolkits, and other resources around designing AI user experiences. I will keep this updated. 7 Steps to AI Products – Allie K. Miller (slide deck) UX in the Age of … Read more
(8) reasons why data visualization training for your BI team may not increase analytics adoption
Customers want simple, well-designed decision support tools and UX’s that are actionable. Businesses want to see value from data and adoption of data-driven decision making. However, the UX that is afforded to is often simply a byproduct of the analytics team’s engineering, or, at best, “data viz” efforts—and it’s not working. A decade later, success rates for data projects remain unchanged, despite vendor/BI tooling improvements. What are BI/analytics teams still missing? Design.
Humans – The Weak Link in your ML / AI Strategy?
In many cases, machine learning needs to be deployed to augment human decision making, not automate it. What are you doing to account for this dependency on the success of your data product?